Information Retrieval

General Information

This web page gives information on the lecture 'Information Retrieval' which is held during the winter term 21/22 by Andreas Nürnberger. A moodle link will be provided, which will contain all the necessary information and content of the course and will be updated regularly. Please note, you need to register via LSF for the exercises.

The details will be sent to students via email after they enrol via LSF!

Information retrieval focuses on obtaining, extracting or mining information from a large collection of unstructured data, e.g. in form of text documents, images or videos. Information retrieval concepts are applied in web search engines, digital libraries and multimedia archives such as image and video databases. In this course the foundations of information retrieval will be introduced and illustrated on some specific application areas.

Master students, please note that this course is 5CP only!

Requirements for Participation in the Final Exam

All students are required to participate in the exercise classes. Every week, there will be an assignment sheet that will be handed out one week in advance. This sheet has to be prepared by every student and will be discussed in class. There are two different types of exercise tasks: theoretical tasks and a programming task. The programming assignments can be solved in small groups of up to three students and must be sent in before the respective deadline. Prerequisites for a written exam and a 'Schein' is fulfillment of the following criteria:

  • at least 66% of individual votes for all theoretical tasks,
  • Submit programming tasks (to be done in group of 3-5) and get 66% of the total programming points (from the TWO mandatory programming assignments, taken together) followed by a short 10 min final team presentation (in Jan/Feb). Programming tasks will be considered only in Java 8 and Apache Lucene 7. For the last task, you can use any web GUI development frameworks but the back-end should be in Apache Lucene/Solr or PyLucene.
  • at least two presentations of a solution in front of the class.

For acquiring the "Schein" you have to write and pass the exam.

A general reminder: In accordance with the examination rules, we offer each student exactly one examination date (oral or written) each term. The registration for a follow-up examination is only possible in the next term (i.e. after 6 months). As soon as a student has registered for an exam, either by using the LSF for written exams or by filling in the information on an examination list for oral exams (or filling out a registration form), this is counted as the agreed examination date. If it is cancelled, the rule above applies.

Dates and Rooms


  Time Start Room
Lecture Thu, 15:00 - 17:00 14.10.2021 G44-H6

Exercise (1st group)

Wed, 17.00-19.00 20.10.2021 G22A-216
Exercise (2nd group) Mon, 13.00-15.00 18.10.2021 G22A-209
Exercise (3rd group) Mon, 15.00-17.00 18.10.2021 G02-109
Exercise (4th group) Thu, 17.00-19.00 21.10.2021 G22A-020
Exercise (5th group) Mon, 15.00-17.00 18.10.2021  G22A-208
Exercise (6th group) Tue, 17.00-19.00 19.10.2021  G22A-216 
Written Exam tba tba tba


Teaching Staff

If you have any questions about the lecture or the exercises, please contact us via e-mail:


Will be provided in Moodle (link to be given).

Additional Materials


  • Introduction to Information Retrieval, C.D. Manning, P. Raghavan, H. Schütze, Cambridge University Press, 2008. (Online-Version)
  • Search User Interfaces, Marti Hearst, Cambridge University Press, 2009. (Online-Version)
  • Soft Computing in Information Retrieval, Fabio Crestani and Gabriella Pasi, Physica Verlag, 2000.
  • Modern Information Retrieval, Ricardo Baeza-Yates and Berthier Ribiero-Neto, Addison Wesley, 1999.
  • Foundations of Statistical Natural Language Processing, Chris Manning and Hinrich Schütze, MIT Press, Cambridge, MA, 1999.
  • Information Retrieval: Data Structures and Algorithms, William B. Frakes and Ricardo Baeza-Yates, Prentice-Hall, 1992.

Last Modification: 22.09.2021 - Contact Person:

Sie können eine Nachricht versenden an: Prof. Dr.-Ing. Andreas Nürnberger